DEFAULTMODEL.
This class represents a simple model which can be used for prototyping ARE equations. You can set up a new model by passing a descr structure, which should contain information about all the data matrices.
Note that the data matrices for Q,R and E have default values and are set to identity matrices with the correct dimensions by default.
Andreas Schmidt, 2016
Definition at line 18 of file DefaultModel.m.
Public Member Functions | |
DefaultModel (ModelDescr descr) | |
function A = | A_coeff () |
function A = | A_comp (md) |
function B = | B_coeff () |
function B = | B_comp (md) |
function C = | C_coeff () |
function C = | C_comp (md) |
function E = | E_coeff () |
function E = | E_comp (md) |
function Q = | Q_coeff () |
function Q = | Q_comp (md) |
function R = | R_coeff () |
function R = | R_comp (md) |
Public Member Functions inherited from ARE.Model | |
virtual function [ A , A , B ] = | B_comp (ModelData model_data, this,ModelData model_data) |
function [
E , A , B , C , Q , R ] = | assemble (md) |
ASSEMBLE Assembles all the data matrices. This function works for both, the reduced and the full model. More... | |
function E = | mass_matrix (md) |
MASS_MATRIX Get the mass matrix of the problem This function is used by the LRFG algorithm for the orthogonalization procedure. More... | |
function g = | gamma (ModelData model_data, dsim) |
GAMMA Calculate the value of gamma. This is used by applying the Lyapunov equation method. More... | |
function R = | R_coeff () |
function Q = | Q_coeff () |
function E = | E_coeff () |
function C = | C_coeff () |
function B = | B_coeff () |
function R = | R_comp (ModelData model_data) |
function Q = | Q_comp (ModelData model_data) |
function E = | E_comp (ModelData model_data) |
function C = | C_comp (ModelData model_data) |
function [
T , y , x ] = | simulate (ModelData model_data, dsim) |
SIMULATE This function simulates the underlying LTI model If you provide dsim, the closed-loop simulation will be performed. More... | |
Public Member Functions inherited from AbstractModel.Model | |
virtual function dsim = | detailed_simulation (ModelData model_data) |
DETAILED_SIMULATION The function DETAILED_SIMULATION returns an instance of SimData and. More... | |
virtual function rsim = | rb_simulation (IReducedData reduced_data) |
REDUCED_SIMULATION This function should return a reduced simulation of type RBSimData. More... | |
function ModelData model_data = | gen_model_data () |
GEN_MODEL_DATA Use this function in order to create a class of type ModelData which contains all the large-scale model data such as the discretized operators. More... | |
function IDetailedData detailed_data = | gen_detailed_data (ModelData model_data) |
GEN_DETAILED_DATA Call the basis generation algorithm. More... | |
function IReducedData reduced_data = | gen_reduced_data (IDetailedData detailed_data) |
GEN_REDUCED_DATA Get the reduced data structures. More... | |
function pt = | problem_type () |
PROBLEM_TYPE Use this function to determine the problem type. So consider overwriting it if necessary! TODO: implement a smart interface that automatically generates the correct. More... | |
function mu = | get_mu () |
Get the parameter values. More... | |
function this = | set_mu (mu) |
Set the parameter values. More... | |
Public Attributes | |
descr | |
mu = "[]" | |
mu_names = {""} | |
mu_ranges = {""} | |
Public Attributes inherited from ARE.Model | |
enable_error_estimator = false | |
calc_residual = true | |
RB_gamma_mode = "Kernel" | |
Additional fields for basis generation: More... | |
RB_gamma_enabled = 1 | |
RB_gamma_settings = {""} | |
p | |
The number of measurement outputs. | |
m | |
The number of control inputs and measurements. | |
n | |
model_data | |
Public Attributes inherited from AbstractModel.Model | |
mu | |
mu_names | |
mu_ranges | |
Public Attributes inherited from Greedy.LRFG.ModelInterface | |
RB_greedy_tolerance = 1e-4 | |
RB_orthonormalize_E = true | |
RB_error_indicator = "residual" | |
RB_pod_tolerance = 0.99 | |
RB_pod_max_extension = 10 | |
RB_M_train = "Uniform" | |